N2 - This paper presents a model environment for construction of patient-specific computational fluid dynamic (CFD) models for the abdominal aorta (AA). Realistic pulsatile velocity waveforms are employed by using in vivo ultrasound blood flow measurements. Ultrasound is suitable for acquisition of blood<br/>velocity profiles, but these are influenced by noise, which will cause convergence problems in CFD simulations. Therefore, physiological smoothing of the velocity profiles is needed. This paper uses the Womersley-Evans model for physiological smoothing of measured blood velocity profiles in the AA. The geometry for the CFD simulation model was obtained by segmentation of MRI scans using a 3 Tesla scanner (Magnetom Trio, Siemens Healthcare, Erlangen, Germany). Spectral velocity data were obtained from a BK Medical ProFocus scanner using a research interface. All data were obtained from healthy volunteers. The estimated and smoothed velocity profiles were quantitatively compared. The energy contained in the velocity profile after smoothing is 65% larger relative to the noise contaminated estimated profiles. In conclusion, a model environment that produces realistic patient-specific CFD simulation models without<br/>convergence issues has been developed. The data processing for the model environment can be performed within six hours which is fast enough to be used in the clinical setting.

AB - This paper presents a model environment for construction of patient-specific computational fluid dynamic (CFD) models for the abdominal aorta (AA). Realistic pulsatile velocity waveforms are employed by using in vivo ultrasound blood flow measurements. Ultrasound is suitable for acquisition of blood<br/>velocity profiles, but these are influenced by noise, which will cause convergence problems in CFD simulations. Therefore, physiological smoothing of the velocity profiles is needed. This paper uses the Womersley-Evans model for physiological smoothing of measured blood velocity profiles in the AA. The geometry for the CFD simulation model was obtained by segmentation of MRI scans using a 3 Tesla scanner (Magnetom Trio, Siemens Healthcare, Erlangen, Germany). Spectral velocity data were obtained from a BK Medical ProFocus scanner using a research interface. All data were obtained from healthy volunteers. The estimated and smoothed velocity profiles were quantitatively compared. The energy contained in the velocity profile after smoothing is 65% larger relative to the noise contaminated estimated profiles. In conclusion, a model environment that produces realistic patient-specific CFD simulation models without<br/>convergence issues has been developed. The data processing for the model environment can be performed within six hours which is fast enough to be used in the clinical setting.